1. Technical Field
The present invention relates in part to a method for ascertaining the quantity or characteristic of a product attribute in process manufacturing, and more specifically, to determining the quality or a characteristic of a food product in the food manufacturing industry. The inventive method disclosed herein utilizes on-line machine vision technology to image a foodstuff coating and through statistical analysis predicts the coating coverage based on the imaged coating concentration of the foodstuff. The methodology could be applied to the on-line measurement of any product attribute through any imaging or sensing medium where a single or multiple correlating signals can be derived.
2. Description of Related Art
The availability of inexpensive and reliable sensors for detecting product attributes while a product is moving along an assembly line or conveyor is a very important factor for successful monitoring and control in process manufacturing environments. For example, the petrochemical industry has made innovative advances in process manufacturing using multivariable modeling, in conjunction with predictive controls, due to readily available, inexpensive sensor equipment such as pressure transducers, thermocouples, and flowmeters which are easily applied to the product streams of the petrochemical industry that mainly consist of gases and liquids during the production phase.
In the past, the solids manufacturing industry encountered greater difficulty in implementing reliable sensor technology during the manufacturing phase. In its most basic form, the solids manufacturing industry used human observers to manually collate, count and determine defective products as they moved along the assembly line. Using human observers was quite expensive, prone to human error and somewhat unreliable. With the advent of digital imaging technology or “machine vision” systems, the solids manufacturing industry now has a reliable, relatively inexpensive, sensor system for monitoring and predicting selected characteristics during the production phase.
In the snack foodstuff industry, the problems of process control and quality control are of paramount importance. Although physical observation techniques have proven somewhat effective, the problem of controlling the amount of coating applied to a foodstuff still exists in the industry. The term coatings, as used herein, may include but is not limited to, seasoning, product ingredients, or other components which are applied to the foodstuff during the manufacturing process. Product coatings may also be applied to the foodstuff in other phases of production, transportation, or distribution.
For example, topical coatings are applied to snack foods to enhance or influence their taste, colour, size, texture and nutritional content. Topical coatings are primarily applied to the foodstuff by several mechanical methods, including dusting, dry coating, spraying oil on baked goods and then dusting a coating on same thereafter. It is known in the art of coating application that the consistency of the flow of coating material to the applicator and the degree of coating adhesion to the foodstuff profoundly affect the consistency of the coatings applied to the foodstuff.
The most common prior art method of quality control is to periodically sample the product and analyze the concentration of coating in a laboratory. Unfortunately, there is usually a large time delay between taking the sample and obtaining the concentration results. Likewise, the sample analysis procedure tends to be slow and destroys the sample itself. Moreover, the coating concentration is often not obtained directly, but determined by measuring the salt concentration of the sample operating on the assumption that the coating concentration and salt concentration remain constant, which is not always the case.
As such, a need in the art exists for a method of comparing product coatings to a desired product characteristic template and reliably predicting the characteristics of the actual product during the production phase in real-time or near real-time. A need also exists for a reliable and inexpensive method for assuring quality control of products manufactured on-line as the product moves from one phase of assembly to another that provides almost instantaneous monitoring and feedback control in an on-line manufacturing environment.
The qualities of texture, taste and sight of a snack food are known in the art as organoleptic properties because they are ordinarily measured by either human perception or mechanical device. These two methods of measurement are normally not useful in on-line feedback control in high-speed production because the time necessary to analyze a sample is too great to provide timely feedback to control the process. Further, the costs of manpower make it cost-prohibitive to use human perception as a feedback control mechanism in most production environments. An image-based soft sensor system predicting organoleptic properties would be ideal in the production of food products. In the prior art, there is virtually no known mechanical method to predict organoleptic qualities.
There are several specific organoleptic properties of interest in the snack food industry including blister level, toast points, taste, texture, crispness, crunchiness, and peak break force. Properties such as blister level, toast points, taste, texture, crispness, and crunchiness are ordinarily measured by human sensory response; the peak break force by mechanical equipment. Toast points are small, black grill marks left by the oven belt on the surface of the chips. Blister level is a measure of the degree of the blistering on the surface of a snack food. A taste property (unrelated to coating level) can be measured by having a human taste a sample product and compare it with a product to be measured. Taste, texture, crispness and crunchiness are all similar attributes and relate to mouth feel of the product. For example, a human first eats a reference product and subsequently eats the product to be evaluated. Peak break force is a mechanical measure of the firmness of the product. The value of peak break force is related to the break strength and hence the required force to bite and/or chew the product. For example, the peak break force is an important factor for snack chips.
Unfortunately, measuring the human sensory response has several drawbacks. First, human measurement is subjective. A large number of human testers would decrease error reporting due to subjectivity, but would increase the cost of obtaining more accurate measurements of organoleptic properties such as taste. Second, it is difficult to implement an on-line feedback control based upon human measurement. There is an impractical lag time between human measurement and feedback to the process, especially in high-speed production environments.
Consequently, a need in the art exists for a method to objectively measure and predict organoleptic properties in products, especially food products. Further, a need exists for a method and apparatus that can use the numeric values of organoleptic properties to provide on-line feedback control in high-speed production.